Erik T. Mueller

Erik Mueller is Senior Director of Intelligent Assistants at Capital One, where he leads teams that develop artificial intelligence capabilities including natural language understanding, dialogue management, natural language generation, generative dialogue, and insight generation. As a member of the original Watson Team at IBM for five years, he co-developed the Watson Jeopardy! system, Watson for Healthcare, and WatsonPaths. He won the AAAI Feigenbaum Prize with the team. He has ten patents on artificial intelligence and is the author of four books in the field. He holds a Ph.D. and M.S. in computer science from UCLA and an S.B. in computer science and engineering from MIT.

March 29, 2016: My patent application with Bagchi, Ferrucci, and Levas "Method of answering questions and scoring answers using structured knowledge mined from a corpus of data" was issued as United States Patent No. 9,299,024 by the USPTO.

July 31, 2015: I've released the code for
DAYDREAMER
and
ThoughtTreasure
on GitHub.
DAYDREAMER is a goal-based agent and cognitive architecture.
ThoughtTreasure is a commonsense knowledge base and architecture for natural language processing.

April 7, 2015: My patent application with Bagchi, Ferrucci, and Levas
"Decision-support application and system for problem solving using a question-answering system"
was issued as
United States Patent No. 9,002,773
by the USPTO.

November 17, 2014:
The second edition of my book
Commonsense
Reasoning was published. It contains new chapters on commonsense
reasoning using unstructured information including the Watson system,
commonsense reasoning using answer set programming, and techniques for
acquisition of commonsense knowledge including crowdsourcing.

December 17, 2013:
My patent application with Rangachari Anand, Lee, and Perez-Cedano
"Expert conversation builder"
was issued as
United States Patent No. 8,612,233
by the United States Patent and Trademark Office (USPTO).

July 16, 2013: I'm a member of the team that won the
AAAI Feigenbaum Prize
"for demonstrating that a synthesis of AI techniques, including symbolic
knowledge representation, natural language understanding, and statistical
machine learning, can achieve human-level performance in real-time
factual question-answering."

July 10, 2013:
My article with Ferrucci, Levas, Bagchi, and Gondek
Watson:
Beyond Jeopardy!
has appeared in the June-July 2013 issue of the
journal Artificial Intelligence.